Delivery app analytics means tracking the data that decides how many orders you win on DoorDash or Uber Eats. Most restaurant brands already see their own sales on each app. However, sales alone rarely explain why orders rise or fall. So this guide splits delivery app analytics into four data areas, with real targets from the apps themselves.

In short, track four areas:

• Operations: how often you are online, and how often orders go wrong.
• Visibility: how easily diners find you, from photos to search position.
• Ratings: what diners say, and how that compares with nearby rivals.
• Market: what competitors charge and offer in each delivery zone.

What Is Delivery App Analytics?

Delivery app analytics combines two kinds of data. First, merchant data comes from your own dashboards, such as Uber Eats Manager or the DoorDash Merchant Portal. Second, marketplace data comes from the public app listings that every diner sees.

Merchant Data vs Marketplace Data

In practice, merchant data shows how you perform. Marketplace data, by contrast, shows why. For example, a sales dip may come from a new rival with a big discount, not from your kitchen. As a result, multi-site brands and virtual brands need both in their delivery app analytics.

1. Operations: Stay Online and Get Orders Right

Operations data comes first, because no other fix works if your store is offline. Uber Eats, for instance, reports “uptime” in its daily order summary. It defines this as the time your tablet is online and accepting orders during typical operating hours. It also reports “pause time” separately.

Order accuracy also matters just as much. DoorDash, for example, tracks an operations quality rate for each store. This counts orders with avoidable cancellations or missing or incorrect items.

So start your delivery app analytics by checking uptime, pause time, cancellations, and accuracy weekly, store by store.

2. Visibility: How Delivery Apps Rank Your Restaurant

Next, look at how easily diners find you. However, apps do not publish their full ranking formulas. Still, they share useful signals.

For example, DoorDash says its “Most Loved” stores share four traits: accurate orders, few cancellations, quality photos and fair pricing. This status, it says, can help stores appear more often on its homepage. It adds that menus with photos see stronger engagement and higher conversion. Similarly, Uber says restaurants with pictures on all menu items can see 88% higher monthly sales.

Beyond photos, your search position can also differ by area and by diner. For instance, a brand might rank first for “pizza” in one zone but far lower nearby. Therefore, good delivery app analytics track where your listings appear for key searches in each zone. In addition, compare your photo coverage and menu structure with the top-ranked rivals there.

3. Ratings: Measure What Diners Say

Ratings shape both rankings and choices. In fact, Michael Luca found a one-star Yelp rise meant 5% to 9% more revenue, mainly for independent restaurants. Meanwhile, Anderson and Magruder studied Yelp ratings. Moving from 3.5 to 4 stars raised the chance of a peak-time sell-out by 19 percentage points.

So treat ratings as a core metric in delivery app analytics:

• Star rating and review count: track both for every site and every brand.
• Complaint themes: group reviews into issues such as cold food, late delivery or small portions.
• Rival ratings: compare your score with the top three rivals in each zone.

Afterwards, fix the most common complaint first. Then watch whether ratings recover over the next few weeks.

4. Market Data: Track Rivals Across Delivery Apps

However, your own dashboards cannot show what rivals do. Yet rival moves often explain sudden changes in your orders. That is why market data completes delivery app analytics.

Pricing, in particular, deserves special care. DoorDash, for instance, counts menu markup toward its “Most Loved” status. So compare your app prices with your in-store prices and with nearby rivals.

Example: How Online Rate Lifted Revenue

One real example shows the impact. At a Deliverect event, Bradley Thomas of Kbox, a delivery-only brand, shared his results. After Kbox coached its host kitchens and offered short-term incentives, its online rate rose 9.3% in three months. Moreover, revenue for its poor-performing group of kitchens rose 15%.

These figures come from Kbox alone, so treat them as one company’s experience. Even so, they show why delivery app analytics should start with simply being online.

A Weekly Delivery App Analytics Dashboard

How FoodSpark Supports Delivery App Analytics

Your app dashboards cover much of the first three areas of delivery app analytics. FoodSpark fills the gap with marketplace data. We collect public menus, prices, offers, fees, ratings, and delivery times from apps such as DoorDash, Uber Eats, and Swiggy. Then we deliver it by city, postcode, or radius as CSV, JSON, or a live API.

To learn more, see our food data API, food aggregator scraping, and competitor price monitoring services. You can also explore more food delivery analytics use cases.

Delivery App Analytics: FAQs

What is delivery app analytics?

It is the tracking of data that affects your orders on delivery apps. This covers operations, visibility, ratings, and the wider market.

What is online rate on delivery apps?

It is the share of opening hours when your store is live and accepting orders. Uber Eats reports a similar metric called uptime.

How do delivery apps rank restaurants?

Apps do not publish full formulas. However, DoorDash links accurate orders, few cancellations, quality photos, and fair pricing to more homepage visibility.

Which delivery app analytics metrics matter most?

Start with uptime, cancellations, missing items, and ratings. Then add rival prices and offers in each delivery zone.

Can I see competitor data on delivery apps?

Yes, from public listings. For example, FoodSpark collects rival menus, prices, offers, fees, and ratings by area.

How do I get a free data sample?

First, tell us the apps, cities, and fields you need. Then FoodSpark sends a free 100-row sample in CSV or JSON.